1. Field of the Invention
The invention relates to a linear image sensing device with image matching function and a processing method thereof, and more particularly to a linear fingerprint sensing device, which contains a memory buffer and an image matching logic (or algorithm) and can continuously process input whole fragment images, temporarily store and output the continuous partial fragment images, and then assembles the continuous partial fragment images into a complete fingerprint image in a manner of stacking the partial fragment images side by side. The whole fragment image has the size equal to that of the sensor area, and the partial fragment image has the size smaller than that of the sensor area. The invention also correlates to the patent applications to one of the inventors: (a) U.S. patent application Ser. No. 10/403,052, filed on Apr. 1, 2003, entitled “CAPACITIVE FINGERPRINT SENSOR,” and published on Oct. 9, 2003 as US20030190061A1; (b) Taiwan Patent Application No. 090112023, filed on May 17, 2001, and entitled “CAPACITIVE PRESSURE MICROSENSOR AND METHOD FOR MANUFACTURING THE SAME AND DETECTING SIGNALS OF THE SAME”, now issued as Invention Patent No. 182652; (c) U.S. patent application Ser. No. 10/414,214, filed on Apr. 16, 2003, and entitled “THERMOELECTRIC SENSOR FOR FINGERPRINT THERMAL IMAGING”; (d) U.S. patent application Ser. No. 10/441,022, filed on May 20, 2003, and entitled “SWEEP-TYPE FINGERPRINT SENSOR MODULE AND A SENSING METHOD THEREFOR”; and (e) U.S. patent application Ser. No. 10/849,775, filed on May 21, 2004, and entitled “CARD DEVICE WITH A SWEEP-TYPE FINGERPRINT SENSOR”.
2. Description of the Related Art
There are many known fingerprint authentication techniques. The use of an ink pad and the direct transfer of ink by the thumb or finger from the ink pad to a recording card is the standard way of making this identification. Then, an optical scanner scans the recording card to get an image, which is then compared to fingerprint images or templates in the computer database. However, the most serious drawback of the above-mentioned method is that the fingerprint identification cannot be processed in real-time, and thus cannot satisfy the requirement of real-time authentication, such as network authentication, e-business, portable electronics products, personal ID cards, security system, and the like.
The method for reading a fingerprint in real-time has become the important issue in the biometrics market. Conventionally, an optical fingerprint sensor may be used to read a fingerprint in real-time. However, the optical fingerprint sensor has some drawbacks like it is large in size and has high power consumption. Consequently, silicon fingerprint sensors, which overcome the drawbacks of the optical sensor and are formed by silicon semiconductor technology, are developed. For example, the capacitive fingerprint sensor with the product model number LCT-C500 available from LIGHTUNING TECH. INC. has the advantage.
Owing to the finger dimension, the sensing area of the conventional silicon fingerprint sensor is large, for example, it is greater than 9 mm*9 mm. Furthermore, owing to the limitations in manufacturing the silicon integrated circuit, only 50 to 70 good dies may be formed in a 6″ wafer. The sensor is expensive to various applications. Thus, this expensive price may restrict the silicon fingerprint sensor in various consumer electronics applications such as notebook computers, mobile phones, personal digital assistants, computer peripheral products, or even personal ID cards embedded with the fingerprint sensor.
In order to overcome the cost problem, it is possible to reduce one-dimensional length of the conventional, two-dimensional (2D) area-type silicon fingerprint sensor to that of the linear sensor structure so as to increase the number of good dies and decrease the price of the sensing device. In this case, the finger sweeps across the sensor surface and the overall finger is sequentially scanned into a plurality of whole fragment images, which are then re-constructed into a complete image.
Mainguet et. al. and Kramer disclose linear fingerprint sensors and methods for reconstructing multiple overlapped whole images into a complete image in U.S. Pat. Nos. 6,289,114 and 6,317,508, as shown in FIGS. 1 and 2. FIG. 1 is a schematic illustration showing the conventional architecture using a linear fingerprint sensor to read images of a fingerprint. The sensor 110 is an array device having a horizontal dimension substantially equal to the width of the finger 120 and a vertical dimensional far smaller than the horizontal dimension, wherein the finger sweeps vertically. Thus, a relative moving speed V between the finger 120 and the sensor 110 is created. That is, the finger 120 sweeps over the surface of the sensor 110 at the speed V. Thus, the sensor 110 can continuously acquire whole fragment images, such as continuous whole fragment images 121a to 121s of FIG. 2A. The continuous whole fragment images 121a to 121s can be outputted to a microprocessor 130 with the data size as shown in FIG. 2B, and then stored in a random access memory (RAM) 140. Thereafter, the microprocessor 130 extracts the continuous fragment images 121a to 121s and reconstructs the fingerprint images according to the software logic stored in a read only memory (ROM) 150. First, the images 121a and 121b are reconstructed into an image 121ab, and then the images 121c and 121ab are reconstructed into an image 121abc, as shown in FIG. 2C. The processes are repeated analogically such that the fragment images 121a to 121s are reconstructed into a complete fingerprint image 122 corresponding to the fingerprint, as shown in FIG. 2D.
This method should acquire a relatively large fingerprint image without using a large-area sensor, and is thus advantageous to the cost reduction, and the enhancement of the recognition quality, such as the low false access rate and the low false rejection rate, which is similar to that obtained by the large-area fingerprint sensor.
However, the architecture and the method of the sensor 110 have some drawbacks. First, hundreds of fragment images have to be acquired within a very short period of time (smaller than 1 second). For example, if the sweeping speed of the finger is 10cm/sec and the specification of the fingerprint sensor is 8*280 (this is the specification of “Atmel Fingerchip”, 500 dpi), the random access memory 140 must have the capacity larger than 600 Kbytes or a larger buffer memory is needed for the subsequent reconstructing process, and the cost of the system is thus increased. The '114 patent combines a first combined image, which is formed by combining a first fragment image with a second fragment image, with a third fingerprint image to form a second combined image. Then, the second combined image is combined with a fourth fingerprint image to form a third combined image. In this case, the memory occupied by the combined image gradually increases, and the buffer memory has to be large enough such that all fingerprint images can be combined.
Furthermore, in order to finish the fingerprint recognizing processes within one second (the typically allowable period is smaller than two seconds) after the finger sweeps over the chip surface, the communication interface between the chip of the sensor 110 and the microprocessor 130 of the terminal system must be an interface, such as a parallel interface having the DMA mode or the express serial interface of USB2.0, having a larger bandwidth. Thus, the typical I2C or low-speed SPI or RS232 interface cannot be adopted for transmission, and the flexibility of the design is limited. The micro processor must be, for example, a DSP because the working speed of the micro processor must be very high.
Ericson discloses a fingerprint sensing device containing a memory buffer in U.S. Patent Publication No. 2003/0021495. The advantage of the '495 patent is that the image transmission of the microprocessor of the terminal system is more flexible. However, the problems in the capacity of the random access memory of the terminal system and in the transmission of the image data within a very short period of time (shorter than one second) through a broadband interface still cannot be solved. The micro processor must be, for example, a DSP because the working speed of the micro processor must be very high. In addition, the '495 patent does not mention how to solve the problem in the subsequent image processing method.